I have some tiff files I obtained from splitting a bigger tiff file using gdal translate. The border tiff files have some nodata values, which I can see in numpy as number 15. I want to manipulate these files as numpy arrays, and then write them back to tiff file. How can I write a numpy array to tiff file, while mantaining the number 15 as the nodata value, so they can be read propertly is GIS programs?
Answer
The two functions from the code snippet below, create_raster
and numpy_array_to_raster
should do the trick. In terms of maintaining the NoData
value from the array in the output raster, that is set on the band(s) of a raster with the .SetNoDataValue()
method which in this code snippet is used in the numpy_array_to_raster
function. For more information about using gdal
& numpy
for raster processing I would highly recommend Chris Garrard's book Geoprocessing with Python and for a quick reference this gdal/ogr cookbook page is a great resource.
import os
from osgeo import gdal
from osgeo import osr
import numpy
# config
GDAL_DATA_TYPE = gdal.GDT_Int32
GEOTIFF_DRIVER_NAME = r'GTiff'
NO_DATA = 15
SPATIAL_REFERENCE_SYSTEM_WKID = 4326
def create_raster(output_path,
columns,
rows,
nband = 1,
gdal_data_type = GDAL_DATA_TYPE,
driver = GEOTIFF_DRIVER_NAME):
''' returns gdal data source raster object
'''
# create driver
driver = gdal.GetDriverByName(driver)
output_raster = driver.Create(output_path,
int(columns),
int(rows),
nband,
eType = gdal_data_type)
return output_raster
def numpy_array_to_raster(output_path,
numpy_array,
upper_left_tuple,
cell_resolution,
nband = 1,
no_data = NO_DATA,
gdal_data_type = GDAL_DATA_TYPE,
spatial_reference_system_wkid = SPATIAL_REFERENCE_SYSTEM_WKID,
driver = GEOTIFF_DRIVER_NAME):
''' returns a gdal raster data source
keyword arguments:
output_path -- full path to the raster to be written to disk
numpy_array -- numpy array containing data to write to raster
upper_left_tuple -- the upper left point of the numpy array (should be a tuple structured as (x, y))
cell_resolution -- the cell resolution of the output raster
nband -- the band to write to in the output raster
no_data -- value in numpy array that should be treated as no data
gdal_data_type -- gdal data type of raster (see gdal documentation for list of values)
spatial_reference_system_wkid -- well known id (wkid) of the spatial reference of the data
driver -- string value of the gdal driver to use
'''
print 'UL: (%s, %s)' % (upper_left_tuple[0],
upper_left_tuple[1])
rows, columns = numpy_array.shape
print 'ROWS: %s\n COLUMNS: %s\n' % (rows,
columns)
# create output raster
output_raster = create_raster(output_path,
int(columns),
int(rows),
nband,
gdal_data_type)
geotransform = (upper_left_tuple[0],
cell_resolution,
upper_left_tuple[1] + cell_resolution,
-1 *(cell_resolution),
0,
0)
spatial_reference = osr.SpatialReference()
spatial_reference.ImportFromEPSG(spatial_reference_system_wkid)
output_raster.SetProjection(spatial_reference.ExportToWkt())
output_raster.SetGeoTransform(geotransform)
output_band = output_raster.GetRasterBand(1)
output_band.SetNoDataValue(no_data)
output_band.WriteArray(numpy_array)
output_band.FlushCache()
output_band.ComputeStatistics(False)
if os.path.exists(output_path) == False:
raise Exception('Failed to create raster: %s' % output_path)
return output_raster
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